If JSPerf is not working, you can also use the library Benchmark.js, which is what JSPerf is based off in the first place, to perform bench-marking on your code. You can find the documentation on the library here: https://benchmarkjs.com/.
ZAP- also known as the Zed Attack Proxy, this tool tests for a wide range of issues and is highly customizable to suit your needs.
Grabber — tests for issues such as file inclusion, XSS, and SQL injections. However, it is slower than other Security Analyzers and should only be used on smaller projects.
Wapiti — tests for both attack and injection vestors. It is more advanced tool and runs via the command line.
If you are going to be mainly dealing with client-side single page applications, then a framework such as Mithril could be your best bet.
Conversely, if you’d like to take part in the server-side of things then Node.js is a great option.
Reference-Counting garbage collection: A naive approach to garbage collection, this algorithm will delete the object place in memory if there are zero other objects referencing it. One limitation of this is that if two objects reference each other, they will both be stuck in an infinite loop of referencing each other, so there neither objects will ever have zero objects referencing them. This is called a cycle and can lead to memory leaks.
“C:\Program Files (x86)\Google\Chrome\Application\chrome.exe” — enable-precise-memory-info
The 1,000,000 character-long string consumes roughly 32 megabytes, averaging 32 bytes per character. The task manager reflects this, as Chrome’s memory usage went from around 300 to 334 megabytes after loading the page. To compare, a character in C++ consumes 1 byte of memory.
The second value of each index is the difference of the heap size before and after the creation of bigArray. The third value is the average memory each number consumes. When bigArray is length 1,000,000, the array consumes roughly 32.5 megabytes, and each number in the array consumes 32.5 bytes on average. Once the array reaches a length of 10 million or more, presumably virtual memory moves parts of the heap into storage. This could explain why the average memory usage drops at this point.
Lastly, it’s important to note that the results were different every time the script was run. The other tabs or number of times the page was refreshed affected the results as well.
Anh Le @anhle697
David Alvarado David Alvarado
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Will Pocklington @pocklingtonWill